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Pushing the Frontier
of AI Research
Pushing the Frontier
of AI Research
The Centre for Artificial Intelligence Research (CAIR) opened on the 2nd of March 2017 and performs fundamental AI research.

Our Research

CAIR is redefining Artificial Intelligence. Green and Transparent.
For All. The Tsetlin Machine is here.


Investing 35 million in green and democratic AI technology

Sparebanken Sør and UiA are collaborating to develop a more equitable and environmentally friendly alternative to the artificial intelligence technology used by major tech companies. 

Game Over? – En podcast om kunstig intelligens

Fremskrittene innen kunstig intelligens skjer så hurtig at det er vanskelig å spå om fremtiden. Se for deg en verden uten en datamaskin på kontoret eller Internett i lomma. 

Research Groups

Tsetlin Machine

The Tsetlin machine research team works on the algorithms, theory, and hardware/software platforms of Tsetlin machines. Our focus is on logical and causal world modeling across multiple modalities, such as images, sound, and natural language. This focus involves logical auto-encoding, convolution, regression, transformer, and reinforcement learning. Our overarching aim is to create ultra-low-power artificial general intelligence solely through transparent logical learning and reasoning.

cair to join us, please contact professor Ole-Christoffer Granmo:

Applied AI

In the Applied AI Innovations Group, our mission is to harness the transformative power of artificial intelligence to create real-world impact. We lead the charge by customizing AI approaches to meet each sector’s requirements and obstacles, and we do so by developing state-of-the-art machine learning models, from complex neural networks to transparent models that provide explicit interpretability. These innovations are utilized in a wide array of research fields, encompassing but not limited to improving practices in agriculture and aquaculture, augmenting cultural creations, enhancing educational techniques, bettering health care results, streamlining industrial operations, deciphering human languages, and refining recommendation engines for heightened accuracy and pertinence. The AAII group is more than just an active participant in applied AI. We are a driving force in the ongoing development of intelligent systems that address the dynamic demands of our world.

cair to join us, please contact professor Morten Goodwin.

AI in Remote Sensing (AIRS)

The AI in Remote Sensing (AIRS) research group, hosted under the CAIR, is committed to pushing the boundaries of AI integration with remote sensing technologies. Our goal is to leverage the potential of AI to elevate the analysis, interpretation, and utilization of data acquired from remote sensing platforms across diverse applications.

cair to join us, please contact professor Turgay Celik:

Reinforcement Learning

This research group focuses on the advancement of reinforcement learning systems, with efforts concentrated on discovering the field of Logical Reinforcement Learning (LRL) and enhancing reinforcement learning schemes. In reinforcement learning, the goal is to improve algorithm efficiency, allowing systems to effectively handle complex sensory inputs such as images and audio. In parallel, the group’s work in logical reinforcement learning aims to provide novel techniques for green and democratic decision-making algorithms, using the benefits of traditional computation chips specialization in logical operations.

A significant aspect of the research involves the combination of the Tsetlin Machine and reinforcement learning techniques. The Tsetlin Machine, known for its simplicity and use of propositional logic, offers clear interpretability and reduced computational demands. By incorporating this machine into reinforcement learning strategies, the group aims to develop transparent systems that are adept at learning from their environment, marking a step forward in the quest for machines that exhibit a level of intelligence and understanding comparable to human reasoning, all within a framework of green and democratic AI.

cair to join us, please contact: 

Associate professor Per-Arne Andersen:


Prof. Ole-Christoffer Granmo
  1. EPSRC: SONNETS – Scalability Oriented Novel Network of Event Triggered Systems. Project Code: EP/X036006/1. Co-Investigator. Read more  
  2. EPSRC: ESTEEM – Exploiting the dynamics of self-timed machine learning hardware. Project Code: EP/X039943/1. Co-Investigator. Read more 
  3. NFR: SecureIoTM – Ultra-low-energy IoT Intrusion Detection Systems using Logic-based Tsetlin Machines. Project code: 342167.  Principal Investigator. Read more  
  4. NFR: CaReLearner – Causal Reasoning with Logical Interpretable Learning. Project Code: 335700. Principal Investigator. Read more
  5. NFR: Logic-based Artificial Intelligence Everywhere – Tsetlin Machines in Hardware. Project Code: 312434. Principal Investogator. Read more
  6. Nokia Bell Labs: Energy-Autonomous Pervasive AI Hardware. Co-Investigator.
  7. NFR: Human-Chatbot Interaction Design. Project code: 270940. Co-Principal Investigator. Read more
  8. NFR: Chatbots supporting user loyalty to service providers. Project Code: 282244. Co-Principal Investigator. Read more
  9. NFR: Social Health Bots – Mastering mental health issues through smart personalised automatic assistance. Project Code: 262848. Co-Investigator and Work Package Manager. Read more
  10. NFR: GHO-DRL – Generic Hydropower Optimization Using Deep Reinforcement Learning. Project Code: 269499. Principal Investigator. Read more
  11. AAUKF: SmartRescue – Smartphones for Coordinated Threat Assessment and Evacuation Planning. Principal Investigator.
Prof. Morten Goodwin
  • Norwegian AI Cloud (INFRASTRUKTUR, 316438, Total budget: 80 MNOK): Development of a state-of-the-art Norwegian AI cloud for advanced AI training.
  • KartAI (BIA, NFR nr. 341319, Total budget: 7 MNOK)
  • AI for Multiformat Universe (IPN, 332274, Total budget: 13.0 MNOK): AI applications for enhancing customer understanding in the entertainment industry.
  • Fjong (BIA, NFR nr. 309977, Total budget: 23.4 MNOK): Automation of areal information planning and building permits.
  • KORNMO (BIA, 309876, Total budget: 7.4 MNOK): Optimization of grain production using satellite and agricultural data.
  • CoastVision (MARIN, 325862, Total budget: 12.2 MNOK): Machine vision applied to coastal imagery and video.
  • CreateView (BIA, 309784, Total budget: 6 MNOK): Visual analytics for sizing and disease detection in fish.
  • Seven(7) Industrial and Public PhDs (each total budget: 4MNOK).
Prof. Lei Jiao

Ongoing Projects: (Founding agent, Project name, Project code, Lei’s role in the project, Project homepage)

  1. NFR: CaReLearner, Causal Reasoning with Logical Interpretable Learning. Project code: 335700. Workpackag co-leader. Read more
  1. EU H2020: RHINOCEROS, starting in autumn 2022. Project code: 101069685. Technical contributor.
  2. NFR: Cyber-physical Threat Monitoring, Localization and Enforcement in Support of Safety Critical Infrastructure and System Operation. Project code: 332528. Work package leader. Read mroe
  1. NFR: AI4Citizens: Responsible AI for Citizen Safety in Future Smart Cities.  Project code: 320783. Work package leader. Read more

  2.  NFR: Logic-based Artificial Intelligence Everywhere: Tsetlin Machines in Hardware. Project code: 312434. Work package leader. Read more